Overview

Dataset statistics

Number of variables10
Number of observations4687
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory334.3 KiB
Average record size in memory73.0 B

Variable types

Numeric9
Boolean1

Alerts

Absolute Magnitude is highly overall correlated with Est Dia in KM(max) and 3 other fieldsHigh correlation
Est Dia in KM(max) is highly overall correlated with Absolute Magnitude and 3 other fieldsHigh correlation
Est Dia in KM(min) is highly overall correlated with Absolute Magnitude and 3 other fieldsHigh correlation
Miles per hour is highly overall correlated with Relative Velocity km per secHigh correlation
Minimum Orbit Intersection is highly overall correlated with Absolute Magnitude and 2 other fieldsHigh correlation
Orbit Uncertainity is highly overall correlated with Absolute Magnitude and 2 other fieldsHigh correlation
Relative Velocity km per sec is highly overall correlated with Miles per hourHigh correlation
Relative Velocity km per sec has unique valuesUnique
Miles per hour has unique valuesUnique
Orbit Uncertainity has 1353 (28.9%) zerosZeros

Reproduction

Analysis started2024-05-13 06:21:09.031208
Analysis finished2024-05-13 06:21:25.841958
Duration16.81 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

Absolute Magnitude
Real number (ℝ)

HIGH CORRELATION 

Distinct269
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.267865
Minimum11.16
Maximum32.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.7 KiB
2024-05-13T11:51:26.027848image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum11.16
5-th percentile18
Q120.1
median21.9
Q324.5
95-th percentile27.2
Maximum32.1
Range20.94
Interquartile range (IQR)4.4

Descriptive statistics

Standard deviation2.890972
Coefficient of variation (CV)0.12982709
Kurtosis-0.53583643
Mean22.267865
Median Absolute Deviation (MAD)2.1
Skewness0.19392467
Sum104369.48
Variance8.3577192
MonotonicityNot monotonic
2024-05-13T11:51:26.310432image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.2 84
 
1.8%
20.8 84
 
1.8%
21 76
 
1.6%
21.6 73
 
1.6%
20.3 71
 
1.5%
20.6 71
 
1.5%
21.3 68
 
1.5%
20.7 67
 
1.4%
21.7 65
 
1.4%
19.4 64
 
1.4%
Other values (259) 3964
84.6%
ValueCountFrequency (%)
11.16 1
 
< 0.1%
13.92 1
 
< 0.1%
14.23 1
 
< 0.1%
14.4 2
< 0.1%
14.5 1
 
< 0.1%
14.6 2
< 0.1%
15.2 3
0.1%
15.3 1
 
< 0.1%
15.38 1
 
< 0.1%
15.4 1
 
< 0.1%
ValueCountFrequency (%)
32.1 1
 
< 0.1%
30.8 1
 
< 0.1%
30.6 2
 
< 0.1%
30.4 1
 
< 0.1%
30 1
 
< 0.1%
29.8 1
 
< 0.1%
29.7 2
 
< 0.1%
29.6 1
 
< 0.1%
29.4 5
0.1%
29.345 2
 
< 0.1%

Est Dia in KM(min)
Real number (ℝ)

HIGH CORRELATION 

Distinct269
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2046042
Minimum0.0010105434
Maximum15.579552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.7 KiB
2024-05-13T11:51:26.560098image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.0010105434
5-th percentile0.0096506147
Q10.033462237
median0.11080388
Q30.25383703
95-th percentile0.66765941
Maximum15.579552
Range15.578542
Interquartile range (IQR)0.22037479

Descriptive statistics

Standard deviation0.3695734
Coefficient of variation (CV)1.8062845
Kurtosis652.59157
Mean0.2046042
Median Absolute Deviation (MAD)0.08765367
Skewness17.670107
Sum958.9799
Variance0.1365845
MonotonicityNot monotonic
2024-05-13T11:51:26.838775image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1529519353 84
 
1.8%
0.1838886721 84
 
1.8%
0.1677084622 76
 
1.6%
0.1272198785 73
 
1.6%
0.2315021222 71
 
1.5%
0.2016299194 71
 
1.5%
0.1460679643 68
 
1.5%
0.1925550782 67
 
1.4%
0.1214940408 65
 
1.4%
0.3503926411 64
 
1.4%
Other values (259) 3964
84.6%
ValueCountFrequency (%)
0.0010105434 1
 
< 0.1%
0.0018388867 1
 
< 0.1%
0.0020162992 2
 
< 0.1%
0.0022108281 1
 
< 0.1%
0.002658 1
 
< 0.1%
0.002914439 1
 
< 0.1%
0.0030517923 2
 
< 0.1%
0.0031956189 1
 
< 0.1%
0.0035039264 5
0.1%
0.0035938089 2
 
< 0.1%
ValueCountFrequency (%)
15.57955241 1
 
< 0.1%
4.37074004 1
 
< 0.1%
3.789264984 1
 
< 0.1%
3.503926411 2
< 0.1%
3.346223745 1
 
< 0.1%
3.195618867 2
< 0.1%
2.424124811 3
0.1%
2.315021222 1
 
< 0.1%
2.231284644 1
 
< 0.1%
2.210828104 1
 
< 0.1%

Est Dia in KM(max)
Real number (ℝ)

HIGH CORRELATION 

Distinct269
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.45750891
Minimum0.0022596438
Maximum34.836938
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.7 KiB
2024-05-13T11:51:27.100663image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.0022596438
5-th percentile0.02157943
Q10.074823838
median0.24776501
Q30.56759685
95-th percentile1.4929318
Maximum34.836938
Range34.834679
Interquartile range (IQR)0.49277302

Descriptive statistics

Standard deviation0.82639125
Coefficient of variation (CV)1.8062845
Kurtosis652.59157
Mean0.45750891
Median Absolute Deviation (MAD)0.19599956
Skewness17.670107
Sum2144.3442
Variance0.6829225
MonotonicityNot monotonic
2024-05-13T11:51:27.384134image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3420109247 84
 
1.8%
0.411187571 84
 
1.8%
0.3750075218 76
 
1.6%
0.2844722965 73
 
1.6%
0.5176544822 71
 
1.5%
0.4508582062 71
 
1.5%
0.3266178974 68
 
1.5%
0.4305662442 67
 
1.4%
0.2716689341 65
 
1.4%
0.7835017643 64
 
1.4%
Other values (259) 3964
84.6%
ValueCountFrequency (%)
0.0022596438 1
 
< 0.1%
0.0041118757 1
 
< 0.1%
0.0045085821 2
 
< 0.1%
0.0049435619 1
 
< 0.1%
0.0059434687 1
 
< 0.1%
0.0065168838 1
 
< 0.1%
0.0068240151 2
 
< 0.1%
0.007145621 1
 
< 0.1%
0.0078350176 5
0.1%
0.0080360009 2
 
< 0.1%
ValueCountFrequency (%)
34.83693825 1
 
< 0.1%
9.773271842 1
 
< 0.1%
8.473054088 1
 
< 0.1%
7.835017643 2
< 0.1%
7.482383761 1
 
< 0.1%
7.145621017 2
< 0.1%
5.420507863 3
0.1%
5.176544822 1
 
< 0.1%
4.989304141 1
 
< 0.1%
4.943561926 1
 
< 0.1%

Epoch Date Close Approach
Real number (ℝ)

Distinct777
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1798806 × 1012
Minimum7.889472 × 1011
Maximum1.473318 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.7 KiB
2024-05-13T11:51:27.647709image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum7.889472 × 1011
5-th percentile8.3759544 × 1011
Q11.0155744 × 1012
median1.2030624 × 1012
Q31.3555584 × 1012
95-th percentile1.4526634 × 1012
Maximum1.473318 × 1012
Range6.843708 × 1011
Interquartile range (IQR)3.39984 × 1011

Descriptive statistics

Standard deviation1.9815397 × 1011
Coefficient of variation (CV)0.16794409
Kurtosis-1.1210677
Mean1.1798806 × 1012
Median Absolute Deviation (MAD)1.661436 × 1011
Skewness-0.29502152
Sum5.5301003 × 1015
Variance3.9264995 × 1022
MonotonicityIncreasing
2024-05-13T11:51:27.917240image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.4691708 × 101218
 
0.4%
1.4213088 × 101217
 
0.4%
1.4239872 × 101216
 
0.3%
1.3317948 × 101216
 
0.3%
1.4166432 × 101216
 
0.3%
1.25559 × 101215
 
0.3%
1.457424 × 101215
 
0.3%
1.3266144 × 101215
 
0.3%
1.1945088 × 101215
 
0.3%
1.4580252 × 101214
 
0.3%
Other values (767) 4530
96.7%
ValueCountFrequency (%)
7.889472 × 10112
 
< 0.1%
7.89552 × 10111
 
< 0.1%
7.901568 × 10114
0.1%
7.907616 × 10116
0.1%
7.922304 × 10113
 
0.1%
7.928352 × 10116
0.1%
7.9344 × 10115
0.1%
7.946496 × 10117
0.1%
7.952544 × 10111
 
< 0.1%
7.958592 × 10118
0.2%
ValueCountFrequency (%)
1.473318 × 101214
0.3%
1.4718492 × 10122
 
< 0.1%
1.4712444 × 10126
 
0.1%
1.4706396 × 10125
 
0.1%
1.4691708 × 101218
0.4%
1.468566 × 101210
0.2%
1.4679612 × 101211
0.2%
1.4665788 × 10128
0.2%
1.465974 × 101214
0.3%
1.4653692 × 101211
0.2%

Relative Velocity km per sec
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct4687
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.970811
Minimum0.33550411
Maximum44.633747
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.7 KiB
2024-05-13T11:51:28.200454image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.33550411
5-th percentile4.3871736
Q18.4328648
median12.917889
Q318.077649
95-th percentile27.870318
Maximum44.633747
Range44.298243
Interquartile range (IQR)9.6447839

Descriptive statistics

Standard deviation7.2932226
Coefficient of variation (CV)0.52203287
Kurtosis0.81028737
Mean13.970811
Median Absolute Deviation (MAD)4.7502365
Skewness0.88787991
Sum65481.191
Variance53.191096
MonotonicityNot monotonic
2024-05-13T11:51:28.884646image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.115834389 1
 
< 0.1%
13.93295825 1
 
< 0.1%
9.816349866 1
 
< 0.1%
4.099021824 1
 
< 0.1%
23.47748135 1
 
< 0.1%
10.5242747 1
 
< 0.1%
11.14307726 1
 
< 0.1%
10.57590343 1
 
< 0.1%
16.16405851 1
 
< 0.1%
12.79370864 1
 
< 0.1%
Other values (4677) 4677
99.8%
ValueCountFrequency (%)
0.3355041122 1
< 0.1%
0.5662447233 1
< 0.1%
0.8001539159 1
< 0.1%
0.8739483443 1
< 0.1%
0.9765405792 1
< 0.1%
0.9862237745 1
< 0.1%
1.041673375 1
< 0.1%
1.090090147 1
< 0.1%
1.321001558 1
< 0.1%
1.396674358 1
< 0.1%
ValueCountFrequency (%)
44.63374663 1
< 0.1%
44.2446891 1
< 0.1%
43.78993311 1
< 0.1%
42.71921555 1
< 0.1%
41.86228367 1
< 0.1%
41.66503508 1
< 0.1%
41.11112845 1
< 0.1%
41.01520491 1
< 0.1%
40.17500562 1
< 0.1%
40.16551123 1
< 0.1%

Miles per hour
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct4687
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31251.307
Minimum750.48915
Maximum99841.228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.7 KiB
2024-05-13T11:51:29.154621image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum750.48915
5-th percentile9813.6686
Q118863.475
median28896.026
Q340437.892
95-th percentile62343.115
Maximum99841.228
Range99090.739
Interquartile range (IQR)21574.417

Descriptive statistics

Standard deviation16314.21
Coefficient of variation (CV)0.52203287
Kurtosis0.81028737
Mean31251.307
Median Absolute Deviation (MAD)10625.804
Skewness0.88787991
Sum1.4647488 × 108
Variance2.6615344 × 108
MonotonicityNot monotonic
2024-05-13T11:51:29.418353image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13680.50994 1
 
< 0.1%
31166.63432 1
 
< 0.1%
21958.19302 1
 
< 0.1%
9169.101918 1
 
< 0.1%
52516.77803 1
 
< 0.1%
23541.75009 1
 
< 0.1%
24925.94952 1
 
< 0.1%
23657.23839 1
 
< 0.1%
36157.38247 1
 
< 0.1%
28618.24685 1
 
< 0.1%
Other values (4677) 4677
99.8%
ValueCountFrequency (%)
750.4891485 1
< 0.1%
1266.632821 1
< 0.1%
1789.864295 1
< 0.1%
1954.935051 1
< 0.1%
2184.423622 1
< 0.1%
2206.083961 1
< 0.1%
2330.119173 1
< 0.1%
2438.422649 1
< 0.1%
2954.948386 1
< 0.1%
3124.220871 1
< 0.1%
ValueCountFrequency (%)
99841.22783 1
< 0.1%
98970.94504 1
< 0.1%
97953.70136 1
< 0.1%
95558.61326 1
< 0.1%
93641.74234 1
< 0.1%
93200.51696 1
< 0.1%
91961.48323 1
< 0.1%
91746.91187 1
< 0.1%
89867.47007 1
< 0.1%
89846.23207 1
< 0.1%

Miss Dist.(kilometers)
Real number (ℝ)

Distinct4661
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38413467
Minimum26609.887
Maximum74781600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.7 KiB
2024-05-13T11:51:29.672587image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum26609.887
5-th percentile3339832.4
Q119959283
median39647712
Q357468628
95-th percentile71153819
Maximum74781600
Range74754990
Interquartile range (IQR)37509345

Descriptive statistics

Standard deviation21811098
Coefficient of variation (CV)0.56779821
Kurtosis-1.1896039
Mean38413467
Median Absolute Deviation (MAD)18729968
Skewness-0.10239378
Sum1.8004392 × 1011
Variance4.7572399 × 1014
MonotonicityNot monotonic
2024-05-13T11:51:29.952387image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68527912 2
 
< 0.1%
51175676 2
 
< 0.1%
38666960 2
 
< 0.1%
36223072 2
 
< 0.1%
42092776 2
 
< 0.1%
60960384 2
 
< 0.1%
33047286 2
 
< 0.1%
71402736 2
 
< 0.1%
63854496 2
 
< 0.1%
73234024 2
 
< 0.1%
Other values (4651) 4667
99.6%
ValueCountFrequency (%)
26609.88672 1
< 0.1%
34052.76953 1
< 0.1%
34605.47266 1
< 0.1%
72171.95312 1
< 0.1%
79384.41406 1
< 0.1%
85540.17969 1
< 0.1%
111065.6328 1
< 0.1%
123836.3516 1
< 0.1%
130302.8438 1
< 0.1%
154408.3594 1
< 0.1%
ValueCountFrequency (%)
74781600 1
< 0.1%
74744960 1
< 0.1%
74731656 1
< 0.1%
74731272 1
< 0.1%
74728128 1
< 0.1%
74706872 1
< 0.1%
74676320 1
< 0.1%
74637656 1
< 0.1%
74620848 1
< 0.1%
74619512 1
< 0.1%

Orbit Uncertainity
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5169618
Minimum0
Maximum9
Zeros1353
Zeros (%)28.9%
Negative0
Negative (%)0.0%
Memory size36.7 KiB
2024-05-13T11:51:30.181324image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q36
95-th percentile8
Maximum9
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.0783066
Coefficient of variation (CV)0.87527438
Kurtosis-1.5658284
Mean3.5169618
Median Absolute Deviation (MAD)3
Skewness0.15476104
Sum16484
Variance9.4759713
MonotonicityNot monotonic
2024-05-13T11:51:30.363079image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1353
28.9%
7 700
14.9%
6 620
13.2%
1 568
12.1%
8 329
 
7.0%
5 321
 
6.8%
2 279
 
6.0%
4 212
 
4.5%
3 182
 
3.9%
9 123
 
2.6%
ValueCountFrequency (%)
0 1353
28.9%
1 568
12.1%
2 279
 
6.0%
3 182
 
3.9%
4 212
 
4.5%
5 321
 
6.8%
6 620
13.2%
7 700
14.9%
8 329
 
7.0%
9 123
 
2.6%
ValueCountFrequency (%)
9 123
 
2.6%
8 329
 
7.0%
7 700
14.9%
6 620
13.2%
5 321
 
6.8%
4 212
 
4.5%
3 182
 
3.9%
2 279
 
6.0%
1 568
12.1%
0 1353
28.9%

Minimum Orbit Intersection
Real number (ℝ)

HIGH CORRELATION 

Distinct3678
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.082320073
Minimum2.06111 × 10-6
Maximum0.477891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.7 KiB
2024-05-13T11:51:30.610786image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum2.06111 × 10-6
5-th percentile0.00143047
Q10.0145851
median0.0473655
Q30.1235935
95-th percentile0.2759711
Maximum0.477891
Range0.47788894
Interquartile range (IQR)0.1090084

Descriptive statistics

Standard deviation0.090299974
Coefficient of variation (CV)1.0969375
Kurtosis1.7573214
Mean0.082320073
Median Absolute Deviation (MAD)0.04026859
Skewness1.474985
Sum385.83418
Variance0.0081540853
MonotonicityNot monotonic
2024-05-13T11:51:30.870403image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0336951 7
 
0.1%
0.012946 7
 
0.1%
0.00223976 6
 
0.1%
0.104736 6
 
0.1%
0.113543 5
 
0.1%
0.0861491 5
 
0.1%
0.000615632 5
 
0.1%
0.0413485 5
 
0.1%
0.0653132 5
 
0.1%
0.0266238 4
 
0.1%
Other values (3668) 4632
98.8%
ValueCountFrequency (%)
2.06111 × 10-62
< 0.1%
1.16032 × 10-51
 
< 0.1%
1.49015 × 10-51
 
< 0.1%
1.73698 × 10-51
 
< 0.1%
2.98546 × 10-51
 
< 0.1%
3.07214 × 10-51
 
< 0.1%
4.42295 × 10-54
0.1%
5.25386 × 10-51
 
< 0.1%
6.91401 × 10-51
 
< 0.1%
7.6176 × 10-51
 
< 0.1%
ValueCountFrequency (%)
0.477891 1
< 0.1%
0.457575 1
< 0.1%
0.455968 1
< 0.1%
0.455459 1
< 0.1%
0.454861 1
< 0.1%
0.449524 1
< 0.1%
0.435734 1
< 0.1%
0.435521 2
< 0.1%
0.433741 1
< 0.1%
0.43275 1
< 0.1%

Hazardous
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
False
3932 
True
755 
ValueCountFrequency (%)
False 3932
83.9%
True 755
 
16.1%
2024-05-13T11:51:31.077426image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Interactions

2024-05-13T11:51:23.556783image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:09.577655image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:11.333507image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:13.056287image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:14.777120image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:16.544063image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:18.530235image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:20.196172image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:21.950127image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:23.722360image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:09.759651image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:11.511133image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:13.233876image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:14.951824image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:16.702611image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:18.703203image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:20.376051image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:22.102923image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:23.937468image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:09.949497image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:11.701738image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:13.432340image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:15.153517image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:16.892829image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:18.890112image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:20.595092image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:22.297920image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:24.130849image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:10.143273image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:11.913000image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:13.624686image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:15.358701image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:17.444723image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:19.095485image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:20.789608image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:22.478664image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:24.337865image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:10.375496image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:12.119729image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:13.830719image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:15.567916image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:17.650143image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:19.294785image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:21.005044image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:22.684022image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:24.513365image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:10.565692image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:12.301076image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:14.007386image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:15.743919image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:17.804657image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:19.469633image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:21.180085image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:22.844588image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:24.687695image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:10.757422image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:12.493182image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:14.199596image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:15.937833image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:17.991148image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:19.645723image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:21.382638image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:23.026773image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:24.905788image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:10.985085image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:12.691545image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:14.413439image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:16.145917image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:18.183199image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:19.844101image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:21.585183image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:23.207760image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:25.093080image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:11.151191image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:12.865896image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:14.586726image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:16.344573image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:18.354981image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:20.019122image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:21.758562image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-13T11:51:23.381242image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-05-13T11:51:31.211827image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Absolute MagnitudeEpoch Date Close ApproachEst Dia in KM(max)Est Dia in KM(min)HazardousMiles per hourMinimum Orbit IntersectionMiss Dist.(kilometers)Orbit UncertainityRelative Velocity km per sec
Absolute Magnitude1.0000.176-1.000-1.0000.382-0.381-0.552-0.3460.696-0.381
Epoch Date Close Approach0.1761.000-0.176-0.1760.073-0.112-0.027-0.1470.214-0.112
Est Dia in KM(max)-1.000-0.1761.0001.0000.0200.3810.5520.346-0.6960.381
Est Dia in KM(min)-1.000-0.1761.0001.0000.0200.3810.5520.346-0.6960.381
Hazardous0.3820.0730.0200.0201.0000.187-0.2900.033-0.3230.187
Miles per hour-0.381-0.1120.3810.3810.1871.0000.0660.362-0.1851.000
Minimum Orbit Intersection-0.552-0.0270.5520.552-0.2900.0661.0000.297-0.2730.066
Miss Dist.(kilometers)-0.346-0.1470.3460.3460.0330.3620.2971.000-0.3150.362
Orbit Uncertainity0.6960.214-0.696-0.696-0.323-0.185-0.273-0.3151.000-0.185
Relative Velocity km per sec-0.381-0.1120.3810.3810.1871.0000.0660.362-0.1851.000

Missing values

2024-05-13T11:51:25.331006image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-13T11:51:25.666757image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Absolute MagnitudeEst Dia in KM(min)Est Dia in KM(max)Epoch Date Close ApproachRelative Velocity km per secMiles per hourMiss Dist.(kilometers)Orbit UncertainityMinimum Orbit IntersectionHazardous
021.60.1272200.2844727889472000006.11583413680.50994462753692.050.025282True
121.30.1460680.32661878894720000018.11398540519.17310557298148.030.186935False
220.30.2315020.5176547895520000007.59071116979.6617987622911.500.043058True
327.40.0088010.01968179015680000011.17387424994.83986442683616.060.005512False
421.60.1272200.2844727901568000009.84083122012.95498561010824.010.034798True
519.60.3195620.71456279015680000010.80884424178.30305158759768.010.272213False
619.60.3195620.71456279015680000010.80884224178.29774858759532.010.272213False
719.20.3841980.85909379076160000024.42188454629.31230819324928.000.098758False
817.80.7320741.63696779076160000017.37378438863.41706553598364.000.109354False
921.50.1332160.29787979076160000012.89961028855.13698722709816.000.016907True
Absolute MagnitudeEst Dia in KM(min)Est Dia in KM(max)Epoch Date Close ApproachRelative Velocity km per secMiles per hourMiss Dist.(kilometers)Orbit UncertainityMinimum Orbit IntersectionHazardous
467724.5000.0334620.074824147331800000014.82657733165.5709005.986602e+0680.017687False
467822.7000.0766580.17141214733180000009.12452920410.6591014.154546e+0760.075850False
467926.3000.0146070.032662147331800000017.27849838650.2724695.824744e+0780.040471False
468023.6000.0506470.113250147331800000013.68735930617.2536474.968394e+0770.086149False
468120.7000.1925550.430566147331800000026.01605858195.3198222.506718e+0710.121499False
468223.9000.0441120.098637147331800000022.15426549556.8755486.187511e+0680.019777False
468328.2000.0060890.01361614733180000003.2251507214.3377729.677324e+0560.006451False
468422.7000.0766580.17141214733180000007.19164216086.9836339.126775e+0660.059972False
468521.8000.1160260.259442147331800000011.35209025393.4890713.900908e+0750.177510False
468619.1090.4006410.895860147331800000035.94685280409.5126506.916986e+0760.051777False